// etc.
  constexpr int64_t kLookupTableFindCostScale = 8;
  constexpr int64_t kLookupTableFindStringKeyCostScale = 16;

  auto value_type = mlir::cast<mlir::TensorType>(op.getValues().getType());
  auto key_type = mlir::cast<mlir::TensorType>(op.getKeys().getType());

  int64_t output_size = InferTensorSize(context, value_type);

  int64_t cost = kLookupTableFindCostScale * output_size;

  void rewrite(mlir::stablehlo::ReduceWindowOp op,
               PatternRewriter& rewriter) const override {
    auto transpose_op = cast<TransposeOp>(op.getOperand(0).getDefiningOp());

    const auto result_type = mlir::cast<TensorType>(op.getResult(0).getType());
    const SmallVector<int64_t> new_result_shape =
        Permute<int64_t>(result_type.getShape(), kNchwToNhwcPermutation);

         * the IP address as a 'Subject Alternative Name' which was deemed far too complicated for our test
         * use case.
         *
         * Additionally, in the rare case that a user or a plugin author truly needs to test with a localhost
         * server, they can use http://127.0.0.1
         */
        if ("127.0.0.1".equals(url.getHost())) {

   * addressed by this method is the case in which {@code T} has parametric nullness -- and thus its
   * value may be legitimately {@code null}.)
   */
  @SuppressWarnings("nullness")
  @ParametricNullness
  static <T extends @Nullable Object> T uncheckedCastNullableTToT(@CheckForNull T t) {
    return t;
  }

  /**
   * Returns {@code null} cast to any type.
   *

   * addressed by this method is the case in which {@code T} has parametric nullness -- and thus its
   * value may be legitimately {@code null}.)
   */
  @SuppressWarnings("nullness")
  @ParametricNullness
  static <T extends @Nullable Object> T uncheckedCastNullableTToT(@CheckForNull T t) {
    return t;
  }

  /**
   * Returns {@code null} cast to any type.
   *

	}
	switch arng {
	case "B8":
		curSize = 0
		curQ = 0
	case "B16":
		curSize = 0
		curQ = 1
	case "H4":
		curSize = 1
		curQ = 0
	case "H8":
		curSize = 1
		curQ = 1
	case "S2":
		curSize = 2
		curQ = 0
	case "S4":
		curSize = 2
		curQ = 1
	case "D1":
		curSize = 3
		curQ = 0
	case "D2":
		curSize = 3
		curQ = 1
	default:

          collected_impl_funcs,
      OpBuilder* builder);

  // Make the decisions based on the subgraphs.
  // It may be the case we cannot decide the best scenarios for the user,
  // in this case, we just return false.
  bool MakeDecisions(ArrayRef<func::CallOp> output_subgraphs);

  // Rewire the subgraphs based on the decisions made.

 */

package org.gradle.internal.classpath;

import com.google.common.annotations.VisibleForTesting;
import com.google.common.collect.ImmutableList;
import org.gradle.api.NonNullApi;
import org.gradle.internal.Cast;
import org.gradle.internal.classpath.intercept.FilterableCallInterceptor;
import org.gradle.internal.lazy.Lazy;

import java.lang.reflect.InvocationTargetException;
import java.lang.reflect.Method;
import java.util.List;

class Capsule final : public Handle {
 public:
  /// Statically cast the TaggedValue capsule to type `T`.
  template <class T>
  T cast() {
    return static_cast<T>(value_.capsule());
  }

 private:
  // Private since it is in general unsafe.
  explicit Capsule(TaggedValue v) : Handle(std::move(v)) {}
  template <class T>
  friend tensorflow::StatusOr<T> tf::libtf::Cast(Handle handle);
};
}  // namespace internal

 *     <li>{@link FixedSupplier}, when the collection is finalized - in that case, the fixed supplier will wrap the realized
 *     of the Java collection this collection property corresponds to</li>
 *     <li>{@link CollectingSupplier}, when the collection is still being added to - in that case,